So, i’ve been noodling around with a number of interesting LLM tools lately. Generative text is… interesting? But the ability to manipulate, cluster, and compare the actual vector embeddings that represent “locations in semantic space” is actually a lot more intriguing.
What I’ve curious about is this: generating raw embeddings (ie, a big list of floats) from a chunk of text is easy. But is there any good way to go the OTHER direction? Like, “describe this embedding in 5 words or less.”